1. Field of the Invention
The present invention generally relates to methods and systems for automated process window characterization and systematic defect detection leveraging persistent wafer imaging.
2. Description of the Related Art
The following description and examples are not admitted to be prior art by virtue of their inclusion in this section.
Inspection processes are used at various steps during a semiconductor manufacturing process to detect defects on wafers to promote higher yield in the manufacturing process and thus higher profits. Inspection has always been an important part of fabricating semiconductor devices. However, as the dimensions of semiconductor devices decrease, inspection becomes even more important to the successful manufacture of acceptable semiconductor devices because smaller defects can cause the devices to fail.
Process window qualification (PWQ) is a type of inspection performed on a specimen fabricated in a particular way that is essential to check if a specific chip design can be manufactured (free of critical hot spots) and to decide about the optimal parameters for a lithography process (e.g., focus/exposure). In currently used methods, the lithography qualification procedure can be a very time consuming and manual procedure. Usually, a focus-exposure modulated wafer is printed to simulate different process window conditions. The wafer is then inspected using a relatively sensitive bright field (BF) inspection tool. The detected defects are divided into bins by a design-based algorithm that classifies the defects by type of printing error (a unique design structure is associated with each bin). To determine how a printing error is affecting the chip yield at different process modulations, a defect sampling strategy followed by scanning electron microscope (SEM) review is performed. For example, a few representative defects from each bin can be visited at different die modulations. This time consuming procedure checks how a structure responds to changes in lithography parameters (focus/exposure) and finally the process window limits are determined. To increase sensitivity, a second iteration is sometimes performed. In that case, the previously identified printing errors can be used as care areas in the wafer inspection. The complete procedure may then be repeated.
There are, however, several disadvantages to currently used methods for PWQ. For example, the currently used methods can be substantially time consuming (several days) and can require engineering expertise and tool time availability (optical inspector and/or SEM review). The tuning of the inspection tool on a modulated wafer involves a lot of trial and error tests to work within the defect count capacity of the optical inspector. The goal is to detect any potential hot spots by exaggerating their formation mechanism (e.g., defocusing) but at the same time the detection system should not run into defect count saturation. Running the inspection at a sensitivity below the sensitivity capability of the inspection tool can compromise the whole wafer analysis. Another disadvantage of the currently used methods is related to the sampling strategy for SEM review. The assumption is that a systematic printing error is accurately represented by a few selected defects/locations observed using SEM review (representative sampling). If the assumption is invalid, hot spots can be missed or process window can be incorrectly reported. An additional weak point of the currently used methods is that patterns that are intended to be identical on the wafer may not be identical on a mask used to print them. In this case, a die-to-die approach would miss the source of the variation.
Accordingly, it would be advantageous to develop systems and methods for detecting defects on a specimen that do not have one or more of the disadvantages described above.